{dm} is fantastic!
A quick overview of the {dm} package for working with relational data models in R.
Zero to consciously incompetent with {Rcpp}
Exploring the world of {Rcpp} through the eyes of a complete novice.
Many models, many plots, many pages!
A quick post showing a cool {knitr} trick you can use when creating a pdf with many plots and many pages.
Musings on the RStudio instructor training process
A few thoughts and reflections on my recent experience completing the RStudio instructor training course.
How has Covid-19 affected UK athletics rankings in 2020?
A look into how Covid has impacted the breadth and depth of athletic performances in the UK in 2020.
When one model is not enough: Stacking models with {stacks}
A few notes on stacking models with {stacks}.
{bitmexr} gets a hex logo!
Steps to create a simple hex logo using the {hexSticker} package.
Investigating sports injuries with Bayesian networks using {bnlearn}
This post explores the use of Bayesian networks with the excellent {bnlearn} package to examine the relationship between different risk factors and the probability of sustaining a sports injury.
Introducing {poweRof10}
A quick introduction to a package I created to scrape data from athletics rankings website www.thepowerof10.info.
Building a python package: Reflections from an R user
In this post I note down some of my experiences with making my first python package, specifically highlighting some of the similarities and differences between R and python when it comes to package building. My hope is that R users looking to expand their pythonic horizons might find something useful!
Build with R, deploy with Python (and Heroku)
This post looks at a cross-language approach to model deployment - something that may come in useful when working within a large data science / production environment.
Penguins and nakedpipes
Exploring the new {palmerpenguins} dataset with {nakedpipe} - An alternative to using {magrittr}'s %>%.
Opening the black box: Exploring xgboost models with {fastshap} in R
Being able to understand and explain why a model makes certain predictions is important, particularly if your model is being used to make critical business decisions. This post takes a look into the inner workings of a xgboost model by using the {fastshap} package to compute shapely values for the different features in the dataset, allowing deeper insight into the models predictions.
bitmexr 0.3.0: Place, modify and cancel your orders on BitMEX without leaving R!
bitmexr 0.3.0 brings some exciting new features to the package. bitmexr now supports placing, editing and cancelling orders through BitMEX's API. In addition, the testnet version of the API is now supported soyou can try out managing orders using the package in a risk free environment!
{tidymodels} workflow with Bayesian optimisation
I've been collecting a few notes on using the tidymodels workflow for modelling, and thought it might be worth sharing them here. More for personal reference than anything, but someone might find my ramblings useful!
Pretty tables with {gt}
Traditionally I have been an ardent user of kable + kableExtra when it comes to creating tables. These packages have served me well, however the CRAN release of a new player in the table package space - gt - promted me to try it out and explore some of the features it had to offer.
bitmexr: An R client for BitMEX cryptocurrency exchange.
How bitmexr came to be.
Exploring the recent Bitcoin crash with {tidyquant} and {gganimate}
Bitcoin recently had a significant sell off, crashing 50% in a matter of hours. This undoubtly was due to the uncertainty in markets surrounding the economic impacts of COVID-19, and the consequent reduction in liquidity faced by many different assets. The volatile price action does however make for an interesting case study which this post will explore.
Writing a thesis in R Markdown
A short discussion about my experiences using R Markdown to write my PhD thesis
Athletics rankings
Using R tools to gather data from an athletics rankings website.
First post
A fresh start (again)